Considerations for Benchmarking Virtual Network Functions and Their Infrastructure

Benchmarking Methodology Working Group (BMWG) has traditionally conducted laboratory characterization of dedicated physical implementations of internetworking functions (or physical network functions, PNFs). The Black-box Benchmarks of Throughput, Latency, Forwarding Rates and others have served our industry for many years. and are the cornerstones of the work. An emerging set of service provider and vendor development goals is to reduce costs while increasing flexibility of network devices, and drastically accelerate their deployment. Network Function Virtualization (NFV) has the promise to achieve these goals, and therefore has garnered much attention. It now seems certain that some network functions will be virtualized following the success of cloud computing and virtual desktops supported by sufficient network path capacity, performance, and widespread deployment; many of the same techniques will help achieve NFV. In the context of Virtualized Network Functions (VNF), the supporting Infrastructure requires general-purpose computing systems, storage systems, networking systems, virtualization support systems (such as hypervisors), and management systems for the virtual and physical resources. There will be many potential suppliers of Infrastructure systems and significant flexibility in configuring the systems for best performance. There are also many potential suppliers of VNFs, adding to the combinations possible in this environment. The separation of hardware and software suppliers has a profound implication on benchmarking activities: much more of the internal configuration of the black-box device under test (DUT) must now be specified and reported with the results, to foster both repeatability and comparison testing at a later time. Consider the following User Story as further background and motivation: "I'm designing and building my NFV Infrastructure platform. The first steps were easy because I had a small number of categories of VNFs to support and the VNF vendor gave HW recommendations that I followed. Now I need to deploy more VNFs from new vendors, and there are different hardware recommendations. How well will the new VNFs perform on my existing hardware? Which among several new VNFs in a given category are most efficient in terms of capacity they deliver? And, when I operate multiple categories of VNFs (and PNFs) *concurrently* on a hardware platform such that they share resources, what are the new performance limits, and what are the software design choices I can make to optimize my chosen hardware platform? Conversely, what hardware platform upgrades should I pursue to increase the capacity of these concurrently operating VNFs?" See http://www.etsi.org/technologies-clusters/technologies/nfv for more background, for example, the white papers there may be a useful starting place. The Performance and Portability Best Practices are particularly relevant to BMWG. There are documents available in the Open Area http://docbox.etsi.org/ISG/NFV/Open/Latest_Drafts/ including drafts describing Infrastructure aspects and service quality.

BMWG will consider the new topic of Virtual Network Functions and related Infrastructure to ensure that common issues are recognized from the start, using background materials from industry and SDOs (e.g., IETF, ETSI NFV). This memo investigates additional methodological considerations necessary when benchmarking VNFs instantiated and hosted in general-purpose hardware, using bare-metal hypervisors or other isolation environments such as Linux containers. An essential consideration is benchmarking physical and virtual network functions in the same way when possible, thereby allowing direct comparison. Also, benchmarking combinations of physical and virtual devices and functions in a System Under Test. A clearly related goal: the benchmarks for the capacity of a general-purpose platform to host a plurality of VNF instances should be investigated. Existing networking technology benchmarks will also be considered for adaptation to NFV and closely associated technologies. A non-goal is any overlap with traditional computer benchmark development and their specific metrics (SPECmark suites such as SPECCPU). A colossal non-goal is any form of architecture development related to NFV and associated technologies in BMWG, consistent with all chartered work since BMWG began in 1989.

This section lists the new considerations which must be addressed to benchmark VNF(s) and their supporting infrastructure. The System Under Test (SUT) is composed of the hardware platform components, the VNFs installed, and many other supporting systems. It is critical to document all aspects of the SUT to foster repeatability.

New Hardware devices will become part of the test set-up. High volume server platforms (general-purpose, possibly with virtual technology enhancements). Storage systems with large capacity, high speed, and high reliability. Network Interface ports specially designed for efficient service of many virtual NICs. High capacity Ethernet Switches. Labs conducting comparisons of different VNFs may be able to use the same hardware platform over many studies, until the steady march of innovations overtakes their capabilities (as happens with the lab's traffic generation and testing devices today).

It will be necessary to configure and document the settings for the entire general-purpose platform to ensure repeatability and foster future comparisons, including: number of server blades (shelf occupation) CPUs caches storage system I/O as well as configurations that support the devices which host the VNF itself: Hypervisor (or other forms of virtual function hosting) Virtual Machine (VM) Infrastructure Virtual Network (which interconnects Virtual Machines with physical network interfaces, or with each other through virtual switches, for example) and finally, the VNF itself, with items such as: specific function being implemented in VNF reserved resources for each function (e.g., CPU pinning) number of VNFs (or sub-VNF components, each with its own VM) in the service function chain (see section 1.1 of for a definition of service function chain) number of physical interfaces and links transited in the service function chain In the physical device benchmarking context, most of the corresponding infrastructure configuration choices were determined by the vendor. Although the platform itself is now one of the configuration variables, it is important to maintain emphasis on the networking benchmarks and capture the platform variables as input factors.

The concept of characterizing performance at capacity limits may change. For example: It may be more representative of system capacity to characterize the case where Virtual Machines (VM, hosting the VNF) are operating at 50% Utilization, and therefore sharing the "real" processing power across many VMs. Another important case stems from the need for partitioning functions. A noisy neighbor (VM hosting a VNF in an infinite loop) would ideally be isolated and the performance of other VMs would continue according to their specifications. System errors will likely occur as transients, implying a distribution of performance characteristics with a long tail (like latency), leading to the need for longer-term tests of each set of configuration and test parameters. The desire for elasticity and flexibility among network functions will include tests where there is constant flux in the number of VM instances. Requests for and instantiation of new VMs, along with Releases for VMs hosting VNFs that are no longer needed would be an normal operational condition. In other words, benchmarking should include scenarios with production life cycle management of VMs and their VNFs and network connectivity in-progress, as well as static configurations. All physical things can fail, and benchmarking efforts can also examine recovery aided by the virtual architecture with different approaches to resiliency.

Since many components of the new NFV Infrastructure are virtual, test set-up design must have prior knowledge of inter-actions/dependencies within the various resource domains in the System Under Test (SUT). For example, a virtual machine performing the role of a traditional tester function such as generating and/or receiving traffic should avoid sharing any SUT resources with the Device Under Test DUT. Otherwise, the results will have unexpected dependencies not encountered in physical device benchmarking. Note: The term "tester" has traditionally referred to devices dedicated to testing in BMWG literature. In this new context, "tester" additionally refers to functions dedicated to testing, which may be either virtual or physical. "Tester" has never referred to the individuals performing the tests. The shared-resource aspect of test design remains one of the critical challenges to overcome in a reasonable way to produce useful results. The physical test device remains a solid foundation to compare against results using combinations of physical and virtual test functions, or results using only virtual testers when necessary to assess virtual interfaces and other virtual functions.

This section discusses considerations related to Benchmarks applicable to VNFs and their associated technologies.

In order to compare the performance of VNFs and system implementations with their physical counterparts, identical benchmarks must be used. Since BMWG has already developed specifications for many network functions, there will be re-use of existing benchmarks through references, while allowing for the possibility of benchmark curation during development of new methodologies. Consideration should be given to quantifying the number of parallel VNFs required to achieve comparable scale/capacity with a given physical device, or whether some limit of scale was reached before the VNFs could achieve the comparable level. Again, implementation based-on different hypervisors or other virtual function hosting remain as critical factors in performance assessment.

When the network functions under test are based on Open Source code, there may be a tendency to rely on internal measurements to some extent, especially when the externally-observable phenomena only support an inference of internal events (such as routing protocol convergence observed in the dataplane). Examples include CPU/Core utilization and Memory Comitted/used. However, external observations remain essential as the basis for Benchmarks. Internal observations with fixed specification and interpretation may be provided in parallel, to assist the development of operations procedures when the technology is deployed, for example. Internal metrics and measurements from Open Source implementations may be the only direct source of performance results in a desired dimension, but corroborating external observations are still required to assure the integrity of measurement discipline was maintained for all reported results. A related aspect of benchmark development is where the scope includes multiple approaches to a common function under the same benchmark. For example, there are many ways to arrange for activation of a network path between interface points and the activation times can be compared if the start-to-stop activation interval has a generic and unambiguous definition. Thus, generic benchmark definitions are preferred over technology/protocol specific definitions where possible.

There will be new classes of benchmarks needed for network design and assistance when developing operational practices (possibly automated management and orchestration of deployment scale). Examples follow in the paragraphs below, many of which are prompted by the goals of increased elasticity and flexibility of the network functions, along with accelerated deployment times. Time to deploy VNFs: In cases where the general-purpose hardware is already deployed and ready for service, it is valuable to know the response time when a management system is tasked with "standing-up" 100's of virtual machines and the VNFs they will host. Time to migrate VNFs: In cases where a rack or shelf of hardware must be removed from active service, it is valuable to know the response time when a management system is tasked with "migrating" some number of virtual machines and the VNFs they currently host to alternate hardware that will remain in-service. Time to create a virtual network in the general-purpose infrastructure: This is a somewhat simplified version of existing benchmarks for convergence time, in that the process is initiated by a request from (centralized or distributed) control, rather than inferred from network events (link failure). The successful response time would remain dependent on dataplane observations to confirm that the network is ready to perform. Also, it appears to be valuable to measure traditional packet transfer performance metrics during the assessment of traditional and new benchmarks, including metrics that may be used to support service engineering such as the Spatial Composition metrics found in . Examples include Mean one-way delay in section 4.1 of , Packet Delay Variation (PDV) in , and Packet Reordering .

It can be useful to organize benchmarks according to their applicable life cycle stage and the performance criteria they intend to assess. The table below provides a way to organize benchmarks such that there is a clear indication of coverage for the intersection of life cycle stages and performance criteria.

For example, the "Time to deploy VNFs" benchmark described above would be placed in the intersection of Activation and Speed, making it clear that there are other potential performance criteria to benchmark, such as the "percentage of unsuccessful VM/VNF stand-ups" in a set of 100 attempts. This example emphasizes that the Activation and De-activation life cycle stages are key areas for NFV and related infrastructure, and encourage expansion beyond traditional benchmarks for normal operation. Thus, reviewing the benchmark coverage using this table (sometimes called the 3x3 matrix) can be a worthwhile exercise in BMWG. In one of the first applications of the 3x3 matrix on BMWG, we discovered that metrics on measured size, capacity, or scale do not easily match one of the three columns above. Following discussion, this was resolved in two ways: Add a column, Scaleability, for use when categorizing benchmarks. If using the matrix to report results in an organized way, keep size, capacity, and scale metrics separate from the 3x3 matrix and incorporate them in the report with other qualifications of the results. This approach encourages use of the 3x3 matrix to organize reports of results, where the capacity at which the various metrics were measured could be included in the title of the matrix (and results for multiple capacities would result in separate 3x3 matrices, if there were sufficient measurements/results to organize in that way). For example, results for each VM and VNF could appear in the 3x3 matrix, organized to illustrate resource occupation (CPU Cores) in a particular physical computing system, as shown below.

The combination of tables above could be built incrementally, beginning with VNF#1 and one Core, then adding VNFs according to their supporting core assignments. X-Y plots of critical benchmarks would also provide insight to the effect of increased HW utilization. All VNFs might be of the same type, or to match a production environment there could be VNFs of multiple types and categories. In this figure, VNFs #3-#5 are assumed to require small CPU resources, while VNF#2 requires 4 cores to perform its function.

Although there is incomplete work to benchmark physical network function power consumption in a meaningful way, the desire to measure the physical infrastructure supporting the virtual functions only adds to the need. Both maximum power consumption and dynamic power consumption (with varying load?) would be useful. >>> ADD REC from Dallas meeting...

Benchmarking activities as described in this memo are limited to technology characterization of a Device Under Test/System Under Test (DUT/SUT) using controlled stimuli in a laboratory environment, with dedicated address space and the constraints specified in the sections above. The benchmarking network topology will be an independent test setup and MUST NOT be connected to devices that may forward the test traffic into a production network, or misroute traffic to the test management network. Further, benchmarking is performed on a "black-box" basis, relying solely on measurements observable external to the DUT/SUT. Special capabilities SHOULD NOT exist in the DUT/SUT specifically for benchmarking purposes. Any implications for network security arising from the DUT/SUT SHOULD be identical in the lab and in production networks.

No IANA Action is requested at this time.

The author acknowledges an encouraging conversation on this topic with Mukhtiar Shaikh and Ramki Krishnan in November 2013. Bhavani Parise and Ilya Varlashkin have provided useful suggestions to expand these considerations. Bhuvaneswaran Vengainathan has already tried the 3x3 matrix with SDN controller draft, and contributed to many discussions. Scott Bradner quickly pointed out shared resource dependencies in an early vSwitch measurement proposal, and the topic was included here as a key consideration. Further development was encouraged by Barry Constantine's comments following the IETF-92 BMWG session: the session itself was an affirmation for this memo with many interested inputs from Scott, Ramki, Barry, Bhuvan, Jacob Rapp, and others.